Comments (4)
yes better than hifi-gan with less training
from istftnet-pytorch.
yes better than hifi-gan with less training
but in my experiments, the stftnet has larger machine noise in the audio, did you have it?
also in the training, there is "max value is tensor(1.1451, device='cuda:0', grad_fn=)
" note
from istftnet-pytorch.
also in the training, there is "max value is tensor(1.1451, device='cuda:0', grad_fn=) " note
Since no activation is applied to spec, only an exp
to make it positive, its upper bound is unlimited, which causes an unlimited bound for the generated audio.
Leaving the spec unbounded is not a good idea.
from istftnet-pytorch.
also in the training, there is "max value is tensor(1.1451, device='cuda:0', grad_fn=) " note
Since no activation is applied to spec, only an
exp
to make it positive, its upper bound is unlimited, which causes an unlimited bound for the generated audio. Leaving the spec unbounded is not a good idea.
How to solve this unbounded problem?
from istftnet-pytorch.
Related Issues (17)
- A multi-gpu training bug HOT 1
- hi. does this repo implements tinyVITS? HOT 1
- Different sample rate HOT 2
- Pretrained models HOT 4
- RuntimeError: istft input and window must be on the same device but got self on cuda:0 and window on cpu HOT 3
- Predicted phase not in range [-pi .. pi], but in range [-1 .. 1] HOT 2
- Directly model complex numbers
- The output channels of the final convolutional layer
- Does anyone know why parameters of C8C1I increases? HOT 2
- Fix TypeError: 'torch.device' object is not callable
- Hard-coded value
- Single frequency line problem HOT 14
- How about the audio quality? HOT 6
- can STFT module convert to onnx format ? HOT 1
- window_sum in stft is just a constant? HOT 3
- A sample as good as HiFiGAN HOT 2
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from istftnet-pytorch.